Researchers decode mood from human brain signals

By developing a novel decoding technology, a team of engineers and physicians at the University of Southern California (USC) and UC San Francisco have discovered how mood variations can be decoded from neural signals in the human brain—a process that has not been demonstrated to date.

Their study, published in Nature Biotechnology, is a significant step towards creating new closed-loop therapies that use brain stimulation to treat debilitating mood and anxiety disorders in millions of patients who are not responsive to current treatments.

Assistant Professor and Viterbi Early Career Chair Maryam Shanechi of the Ming Hsieh Department of Electrical Engineering and the Neuroscience Graduate Program at USC led the development of the decoding technology, and Professor of Neurological Surgery Edward Chang at UCSF led the human implantation and data collection effort. The researchers were supporting the Defense Advanced Research Projects Agency's SUBNETS program to develop new biomedical technologies for treating intractable neurological diseases.